Systems and methods for identifying and capturing potential bankcard spending

ABSTRACT

The invention provides a method and system for a financial institution for capturing the business of a financial services customer. The system may include a data access system for obtaining and storing data; and an analysis system for processing the data. The analysis system (1) selects a study group of customers from the data; (2) observes the study group so as to produce a profile of each study group customer&#39;s financial information; (3) produces a mathematical representation of an interrelationship between study group customers&#39; profiles and the data; (4) applies the mathematical representation to customers not within the study group in order to estimate those customers&#39; profiles; (5) identifies a portion of the customer&#39;s monetary flow eligible to be conducted through the financial institution, the identification based in part on the customer&#39;s profile; and (6) does not require direct input from the customer. The system may further include a marketing system for producing, outputting and implementing a marketing strategy; and storage systems. In addition, the analysis system may utilize processing including producing a profile of the customer&#39;s financial information, the profile including an itemization of the customer&#39;s monetary inflow and outflow; and identifying a portion of the customer&#39;s monetary flow eligible to be conducted through the financial institution, the identification based in part on the customer&#39;s profile.

BACKGROUND OF THE INVENTION

Bankcards, such as credit cards, debit cards, and various others, are inwide use in the current market place. Encouraging individuals toincreasingly utilize bankcards to make purchases is a complicatedchallenge faced by financial institutions. A financial institutionencounters significant competition when attempting to acquire newcustomers and increase the institution's share of existing customers'card spending.

Typically, acquiring new customers and growing the share of a customer'sspending involves marketing strategies based on industry rules of thumband targeting of customers according to broad categories. This lack ofindividualization for marketing, commonly employed by financialinstitutions, has curtailed efforts to acquire new customers and grow aninstitution's share of existing customers' spending.

The known technology is lacking in this respect.

SUMMARY OF THE INVENTION

The invention provides a method and system for a financial institutionfor capturing the business of a financial services customer. The systemmay include a data access system for obtaining and storing data; and ananalysis system for processing the data. The analysis system (1) selectsa study group of customers from the data; (2) observes the study groupso as to produce a profile of each study group customer's financialinformation; (3) produces a mathematical representation of aninterrelationship between study group customers' profiles and the data;(4) applies the mathematical representation to customers not within thestudy group in order to estimate those customers' profiles; (5)identifies a portion of the customer's monetary flow eligible to beconducted through the financial institution, the identification based inpart on the customer's profile; and (6) does not require direct inputfrom the customer. The system may further include a marketing system forproducing, outputting and implementing a marketing strategy; and storagesystems. In addition, the analysis system may utilize processingincluding producing a profile of the customer's financial information,the profile including an itemization of the customer's monetary inflowand outflow; and identifying a portion of the customer's monetary floweligible to be conducted through the financial institution, theidentification based in part on the customer's profile. Any of a widenumber and variety of customers and study groups may be utilized in theprocessing of the invention.

BRIEF DESCRIPTION OF THE DRAWINGS

The present invention can be more fully understood by reading thefollowing detailed description together with the accompanying drawings,in which like reference indicators are used to designate like elements,and in which:

FIG. 1 is a high level flowchart showing a marketing process inaccordance with one embodiment of the invention;

FIG. 2 is a flowchart showing further details of the “determineavailable net cash flow” step of FIG. 1 in accordance with oneembodiment of the invention;

FIG. 3 is a flowchart showing further details of the “Top Down Analysis”step of FIG. 2 in accordance with one embodiment of the invention;

FIG. 4 is a flowchart showing further details of the “Bottom UpAnalysis” step of FIG. 2 in accordance with one embodiment of theinvention;

FIG. 5 is a flowchart showing further details of the “determine spendingprofile” step of FIG. 1 in accordance with one embodiment of theinvention;

FIG. 6 is a flowchart showing further details of the “identify potentialcredit card business” step of FIG. 1 in accordance with one embodimentof the invention;

FIG. 7 is a flowchart showing further details of the “formulatemarketing strategy” step of FIG. 1 in accordance with one embodiment ofthe invention;

FIG. 8 is a flowchart showing further details of the “update loop” stepof FIG. 1 in accordance with one embodiment of the invention;

FIG. 9 is a block diagram showing a spend system in accordance with oneembodiment of the invention;

FIG. 10 is a block diagram showing further details of the spend system,and in particular the customer cash flow analysis module, in accordancewith one embodiment of the invention;

FIG. 11 is a block diagram showing further details of the spend system,and in particular the analysis module, in accordance with one embodimentof the invention;

FIG. 12 is a block diagram showing further details of the spend system,in accordance with one embodiment of the invention;

FIG. 13 is a diagram showing details of a spending profile, inaccordance with one embodiment of the invention;

FIG. 14 is a diagram showing details of a spending profile, inaccordance with one embodiment of the invention; and

FIG. 15 is a table listing acronyms as discussed herein, in accordancewith aspects of the invention.

DETAILED DESCRIPTION OF THE INVENTION

Hereinafter, various aspects of embodiments of the invention will bedescribed. As used herein, any term in the singular may be interpretedto be in the plural, and alternatively, any term in the plural may beinterpreted to be in the singular.

What is disclosed herein is a system and method for identifying andcapturing potential bankcard spending. The invention uses innovativetechniques to obtain highly individualized and detailed assessments of acustomer's financial profile. The invention produces a marketingstrategy that is highly effective and readily implemented. The inventioncan be supported using relatively simple hardware and software.

Various embodiment set forth herein are described in the context of a“credit card” and associated processing. However, it is understood thatthe invention has a much broader field of applicability. For example,with regards to financial transaction tools, the invention (and variousfeatures thereof) pertain to any type of bankcard or account, such asdebit cards, check cards, automated clearing houses, automated tellermachines, online banking channels, and personal financial tools, forexample, among many others.

FIG. 1 is a high level flow chart in accord with one embodiment of theinvention which begins at step 1. Then, the process passes to step 100.In step 100, the process identifies a target, such as for example, anindividual, household, institution, small business, large business,division, team, unit, or any other type of potential customer or currentcustomer (or any breakout/subpart of such potential customer or currentcustomer). Hereinafter a “customer” includes any of such targets.

Step 200 then determines how much of that customer's finances can beconsidered “available net cash flow” (ANCF). In some instances acustomer's ANCF can be summarized as the customer's “ability to pay” forgoods or services they desire to purchase. The determination of acustomer's ANCF may be achieved through a variety of methods or a fusionof various methods. One embodiment of the invention determines acustomer's ANCF by calculating the precise budget of that customer, asbased on that customer's income and expenses, for example. Since thisapproach starts with overall income and subtracts various budgetaryitems until the ANCF is estimated, this approach is herein referred toas a “top down” approach.

One embodiment of the invention determines customers' ANCF by firstthoroughly studying the spending and financial behaviors of a controlledgroup of customers. This study then provides a basis of comparison towhich other customers outside of the study group are compared accordingto a variety of their characteristics, such as, for example, theirfinancial attributes. The ANCF of these other customers is thendetermined by comparing the variety of characteristics of thesecustomers to those of the study group. Since this method starts with anumber of customer characteristics of a customer and builds up to theestimate of ANCF of that customer, this approach is herein referred toas a “bottom up” approach.

In accordance with one embodiment, step 300, of FIG. 1, determines acustomer's spending profile (SP). The spending profile capturescharacteristics of that customer's spending that will facilitatemarketing products to that customer. The spending profile of a customermay be related to the ANCF of a customer. For example, a customer whosespending profile indicates that they spend more than their ANCF may haveto “reign in” his spending habits before he encounters a difficultfinancial situation. Fluctuations in spending may also occur when acustomer opens a new account and runs up a high balance initially, orwhen a customer is going bankrupt. One embodiment of the inventiontherefore produces a continuous, numeric output at an individual levelof a customer's steady state ability to spend. Such an output is notsusceptible to misleading temporary imbalances in a customer's spendingbehavior, spending profile or ANCF.

After step 300 of FIG. 1, the process passes to step 400. Step 400illustrates how one embodiment identifies the potential credit cardbusiness (PCCB), or portion of a customer's spending that could beacquired by the financial institution. In the case of credit cards, thespending profile may be used to determine a customer's ability to spendusing credit cards (ASCC) from the ANCF. This ASCC then forms the basisfor the potential credit card business. In one embodiment, the PCCB of acustomer is related to that customer's spending profile and ANCF. Inaccordance with one embodiment, a financial institution identifies thepotential credit card business on the basis of whether the customercould be encouraged to spend more (of the customer's ANCF) by offeringproducts attractive to the customer. Further, an embodiment identifiesthe potential credit card business based on the possibility of enticinga customer to change her spending profile, for example by shiftingspending to that financial institution from another institution.

In accordance with one embodiment, step 500 formulates a marketingstrategy (MS) for an individual customer. In one embodiment, themarketing strategy is related to the potential credit card business ofan individual customer and is designed to acquire the potential creditcard business of that customer. In other embodiments the marketingstrategy is designed to achieve other objectives such as increasedcustomer satisfaction with the financial institution. In determining amarketing strategy, one embodiment takes into account the marketingtactics available to the financial institution and the constraints onmarketing approaches, among other considerations.

The invention enables the execution of a marketing strategy (EMS) instep 600. In step 700, some embodiments update the marketing strategyunder a variety of circumstances. These updates are continuous oroccasional and account for changes in a customer's behavior, changesexternal to the customer, as well as effects brought about by theexecution of the marketing strategy (EMS). Hereinafter the high levelmethod steps set forth above are described in greater detail.

FIG. 9 provides a high level block diagram of one embodiment of thespend system 800 that performs the methods of the invention. The spendsystem 800 includes an analysis module 810, a data access module 850, acustomer profile data store module 860, a memory portion 870 and amarketing module 880. As shown in FIG. 9, the analysis module 810includes a Customer Cash Flow Analysis Module 820, Spending AnalysisModule 830 and Business Analysis Module 840, in accordance with oneembodiment of the invention.

The invention utilizes a variety of data from sources both internal andexternal to the financial institution. The data access module 850accesses this data. For illustrative purposes, this data may be derivedfrom sources such as: financial records for customers of theinstitution, financial summaries available when underwriting newapplications, the credit bureau, companies specializing in assemblingdossiers of financial information, state and county property records anddemographics sources, for example. The data access module 850 accessesthese sources and retrieves data such as: customer income (salary, giftsor monies from investments for example), wealth such as investments andretirement funds, retail deposit information, debt, expenses (mortgagepayments, utilities or groceries for example), taxes (federal, state,local), home value data, past spending habits, average absolute changein bankcard trade balance, highest bankcard line, credit limits of openmortgage trades, utilization rate of open bankcard trades, discretionaryspending index, value of vehicles owned, demographic clusters, maximumbalance on bankcards and demographic information, for example. The dataaccess module 850 may then output the obtained data, so as to make suchdata available for utilization by other modules of the spend system 800.

Returning to the processing of FIG. 1, the “determine available net cashflow” step 200 of FIG. 1 is shown in greater detail in FIG. 2. Inaccordance with one embodiment, the sub-process shown in FIG. 2 startsat step 210 and then passes to a decisioning step. That is, in step 211,the processing provides a choice of whether to perform top down orbottom up analysis. As is illustrated by FIG. 2, the method may includeany combination of the top down or bottom up analysis. For example, themethod may proceed from step 211 to perform the top down analysis 212.After performing the top down analysis the method may then proceed tostep 216 or back to step 214 to perform the bottom up analysis. The “andnot yet performed” in the processing of steps 213 and 215 reflect thatif the bottom up analysis has already been performed upon thedecisioning of step 213 (or the top down analysis has already beenperformed upon the decisioning of step 215), then the process passes tostep 216.

After either of steps 213 or 215, the process passes to step 216. Instep 216, the process synthesizes, as needed, the results of thecomputational method to produce a determination of a customer's ANCF.That is, if both a bottom up analysis and a top down analysis wasperformed, then the step 216 synthesis the results of that processing.The process then passes to step 219, and returns to step 300.

In accordance with one embodiment, FIG. 3 provides the details of thetop down analysis 212. Generally speaking, the top down analysis 212calculates the precise budget of a customer based on that customer'sincome and expenses. This top down approach starts at step 220 andproceeds to step 221, where the method inputs the data in the dataaccess module 850 pertaining to a customer's income. In one embodiment,step 221 uses the customer's income per month. The next step 222assesses monthly expenses not paid by credit cards. In one embodiment,these expenses are identified because they are not considered to beeligible (i.e., eligible for credit card payment), acceptable ortypically paid with a credit card. A possible example of such an expenseis a mortgage payment. Since the income and expense data may havesignificant variability month to month, the method may smooth theestimates by using a six month average, for example. Then, asillustrated in step 223, these expenses are subtracted from income. Thisprocessing, as reflected by step 224 of FIG. 1 3, results in thatcustomer's available net cash flow (ANCF).

After step 224, the process passes to step 225. In step 225, the, theprocess returns to step 213 of FIG. 2.

FIG. 4 illustrates in greater detail the bottom up analysis of step 214in FIG. 2, in accordance with one embodiment. This process begins atstep 230. Then, in step 231, the process includes identifying a controlgroup for in depth study of their spending habits. In some cases, it isdesirable to obtain data for every financial activity for every memberof the control group. Complete capture of control group financial datacan be achieved, for example, by constructing the control group out ofcustomers who perform all of their financial transactions with thesingle financial institution. In such a situation, the financialinstitution has complete visibility of the customers' spending andincome. Thus, such a thorough visibility of the person (with all theirfinancial transactions with a single financial institution) allowseffective extrapolation of that person's behavior, so as to understandand anticipate other person's behavior, for example.

Next, in step 232, the process includes measuring the spending of thecontrol group. This may include taking rigorous data on their spendingbehaviors. Such data is similar to that previously mentioned, but can bemore or less detailed. Then, in step 233, analysis of the controlgroup's spending forms the basis for the development of a predictivemodel to relate customer spending behavior to ANCF. After step 233, theprocess passes to step 234.

In step 234, external data is incorporated into the data of the controlgroup, to the extent that such data is available (or desired to beutilized with the control group data).

Then, in step 235, the observations of the control group 234 as well asthe analysis of the control group's spending 233 are incorporated into amodel. The development of a model to depict the relationship between thecontrol group member spending and ANCF can be implemented in a number ofappropriate techniques. Such techniques include but are not limited toregression, classification, cluster analysis, discriminant analysis,factor analysis, neural networks, logistic regression, statisticalanalysis, statistical forecasting, case based analysis, rule basedanalysis, and/or other techniques, for example.

In one embodiment, the model establishes a relationship between ANCF andother parameters. For example, the model might establish a relationshipbetween ANCF vis-à-vis average monthly taxes, dinners out per month, andtuition per month, as follows:ANCF=α*(average monthly taxes)+β*(dinners out per month)+χ*(tuition permonth)

-   -   where α, β and χ represent constants determined through the        model development process 235.        Thus, the model may yield the identification of key known        parameters (of a target customer), which may then be used to        estimate unknown parameters (of the target customer).

That is, once the model is developed, the model provides a basis forpredicting the ANCF of customers not studied in the control group, asreflected in step 236. For example, in one embodiment, data obtainedfrom the data access module 850 is then input into the model to estimatethe customer's ANCF. Then, in step 237, the customer's estimated ANCF isoutput.

After step 237, the process passes to step 238. In step 238, the processreturns to step 215 of FIG. 2.

FIG. 10 is a block diagram showing the customer cash flow analysismodule 820 in greater detail, in accordance with one embodiment. Asshown, this embodiment includes a data interface module 824, top downmodule 821, bottom up module 825 and a cash flow analysis computingportion 829. In one embodiment, the cash flow analysis module 820computes ANCF for a customer. The customer cash flow analysis module 820has portions specifically designed for certain computation methods. Forexample, the top down module 821 includes a customer finances data storeportion 822 for storing detailed finance information for each customer.The customer finances computing portion 823 is capable of calculatingthe ANCF of a customer at least partially based on the data stored inthe customer finances data store portion 822.

Further, in accordance with one embodiment, the bottom up module 825 isdesigned to perform the detailed analysis of the control group andassociated predictive model development. The bottom up module thereforeincludes a control group data store portion 828, control group modelcomputing portion 827 and a customer comparison computing portion 826.The control group model computing portion 827 constructs a predictivemodel based at least in part on the data stored in the control groupdata store portion 828. The customer comparison computing portion 826applies the predictive model developed by the control group modelcomputing portion to customer data in order to estimate that customer'sANCF, for example.

In accordance with one embodiment, the data interface module 824 allowsother portions of the customer cash flow analysis module 820 to isolatespecific customer finance data in an appropriate data portion (forexample the data access module 850). The customer cash flow analysismodule 820 has a computing portion 829 that synthesizes and organizesthe operations and computations of the modules contained within thecustomer cash flow module 820. In accordance with one embodiment, thecash flow analysis computing portion 829 may interface with both the topdown module 821 and bottom up module 825 and reconcile differences intheir outputs.

FIG. 5 is a flowchart showing further details of the determine spendingprofile step 300 of FIG. 1, in accordance with one embodiment of theinvention. The sub-processes of FIG. 5 break down the customer'sspending according to spending characteristics that may later be helpfulin marketing products to that customer. For example, one embodiment instep 312 determines how much a customer spends and step 313 determinesthat customer's propensity to spend. For example, some customers mayhave a low propensity to spend even though they are high spenders simplybecause they have an enormous amount available to spend, spend only asmall portion of it, but that small portion is of significant magnitude.Another example is a customer with a high propensity to spend. Thatcustomer may readily make new purchases if given the appropriateopportunity and incentives. In some embodiments, the determination ofthe propensity to spend may be a determination of the percentage of acustomer's ANCF that they spend.

Further, in step 314, one embodiment assesses a customer's total spendusing credit cards. Step 315 estimates that customer's propensity tospend using credit cards and integrates that information into thecustomer's spending profile. One illustration of these concepts is acustomer who spends a significant portion of their ANCF, but strictlyuses cash. This customer is considered to have a high propensity tospend but has a low propensity to spend with credit cards. In accordancewith one embodiment, step 316 further analyzes a customer's credit cardspending characteristics by determining the customer's spending onparticular credit cards.

In accordance with one embodiment, FIG. 13 illustrates how some of thesecharacteristics are manifest in a spending profile. Firstly, FIG. 13shows a breakdown of a customer's spending by method (cash, check, bank1 card, bank 2 card 1, bank 2 card 2). Thus, the bank 1 card accountsfor 31% of the customer's spending. FIG. 13 also illustrates anotherslice of information from the spending profile in which the customer'sspending through the bank 1 card is categorized according to thepurchase amount for each purchase made on that card. Therefore, 24% ofthe customer's monthly purchases using the bank 1 card are between theamounts of $75 and $200.

It is appreciated that the categorization of the customer's spendingthrough the bank 1 card may or may not be representative of the “bank 2card 1” and the “bank 2 card 2” cards. In particular, it is appreciatedthat it may well be the case that different cards are routinely andconsistently used for different purposes. Customers may well havefractional or compartmentalized spending. For example, a particular cardmay always be used for gas purchases, whereas another card is routinelyused for purchases at a outlet store. Such might be the case due to aparticular relationship between the merchant vis-à-vis the card, e.g.such as the merchant only takes that particular card of the customer, orfor some other reason.

In particular, in accordance with aspects of the invention, it may wellbe the situation (as shown in FIG. 13) that there is indeed relativelycomplete visibility into one of the customer's (i.e., Bank 1 card), butnot into the customer's other cards. Thus, the invention uses what datais known across “all the cards” of the customer, and analyzes such datato further understand what is not known about a customer's card (orother spend related information). Once attributes of the customer'sother cards are known (to the extent possible) then target marketing maybe effected, tailored specifically to those known attributes.

In accordance with one embodiment, FIG. 14 further illustrates aspectsof a customer's spending profile. For example, the spending profile forthat customer would indicate that 20% of the customer's spending isattributable to software purchases. One skilled in the art understandsthat a financial institution could extract these characteristics andmany others from the previously mentioned data as well as other datasources. In one embodiment, even though access to the customer's otheraccount information is not readily possible, the embodiment drawsinferences from the available data in order to establish a more completepicture of that customer's spend. For example, the financial institutionmay observe a balance transfer from a different institution's creditcard or a payment to that institution. These observations areinterpreted as spend through that institution and are therefore relevantto the customer's spending profile. One embodiment assesses the spendthrough various credit card accounts by reviewing the financial summaryobtained when the customer opened the credit card account with thefinancial institution. Such a report, for example, provides insight intothe spending behavior of the customer. Referring again to FIG. 5, step317 assembles these characteristics, in addition to numerous others asdesired by the financial institution, into a spending profile for thecustomer. As previously illustrated, this detailed spending profilerepresents an increased understanding of customers' spending preferencesand behaviors. The method then returns to step 400 (of FIG. 1).

FIG. 11 contains a block diagram depicting the spending analysis module830, according to one embodiment. This module includes a data interfacemodule 831, spend type identification portion 832, spend methodidentification portion 833 and a spending analysis computing portion834. The data interface module 831 enables access to data by interfacingwith the data access module 850. The spend type identification portion832 and the spend method identification portion 833 process the dataobtained by the data interface module 831 in accordance with the spendprofile characteristics desired in the particular embodiment. Thespending analysis computing portion 834 analyzes the data processed inthe spend type identification portion 832 and the spend methodidentification portion 833, as well as other data as seen fit, andproduces a spending profile for the customer.

The spending profile is stored in the customer profile data store module860 previously mentioned in FIG. 9. One embodiment of the customerprofile data store module 860 is shown in further detail in the blockdiagram of FIG. 12. Therein the customer profile data store module isshown to include an available to spend data store portion 862, spendingprofile data store portion 864 and a potential credit card business datastore portion 866. The customer profile data store module 860 istherefore capable of storing a dossier of information for each customer,where the information may be created through analysis of the spendsystem 800 or acquired directly from other sources.

FIG. 6 is a flowchart that illustrates one embodiment of the methods ofthe invention. These method steps identify potential credit cardbusiness for the financial institution on an individual customer level.Step 412 of the potential credit card business identification processleverages the product of the ANCF analysis. Step 413 similarlyincorporates the spending profile analysis into the identification ofthe potential credit card business. For example, as shown in step 414,one embodiment is particularly concerned with credit card spending andtherefore determines the customers available to spend on credit cards.Such a determination for an individual customer provides the financialinstitution with an estimate of what further business could be acquiredfrom that customer, for example.

Expanding a financial institution's business with a customer may occurin a number of different fashions. In accordance with one embodiment,step 415 implements the potential credit card business model to identifypotential opportunities to shift that customer's spending to thefinancial institution from another institution. For example, thepotential credit card business model identifies such an opportunity byobserving in the customer's spending profile that the customer alwaysspends using the credit card with the highest rewards when making amajor purpose, such as purchasing a new car. Therefore, the customer isdemonstrating a preference for a credit card attribute that thefinancial institution is able to meet, and that amount of spending istherefore deemed the potential credit card business. Step 415 may alsoidentify the potential credit card business as opportunities to simplyincrease the customer's spending. In accordance with one embodiment, thepotential credit card business model identifies that the customer has anapparent surplus of ANCF. The spending profile of the customer revealsthat although the customer has a few particular hobbies or pastimes, thecustomer is averse from spending significantly on those hobbies,possibly due to cognitive reluctance or guilt associated with luxuryexpenses. The potential credit card business model identifies thesecharacteristics in the spending profile and indicates the possibility ofunleashing the surplus ANCF with financial products that reward thecustomer for spending on a particular hobby. Thus, the potential creditcard business in one embodiment is achieved not by displacing thecustomer's current spending habits but by encouraging additionalspending. After the implementation of the potential credit card businessmodel in step 415, step 416 outputs the customer's potential credit cardbusiness, and the method returns to step 500.

The identification of potential credit card business on an individualcustomer basis provides the financial institution with a competitiveadvantage that can be exploited by the appropriate marketing strategy.FIG. 7 is a flowchart that depicts one embodiment of a method forproducing a marketing strategy. The method allows for the incorporationof germane inputs to the marketing formulation, and these inputs mayvary greatly from embodiment to embodiment.

In FIG. 7, step 512 shows the input of marketing resource constraints.Resource constraints may include limitations on marketing expenses orthe duration of a marketing promotion, among many others. Step 513depicts the input of marketing objectives. Previously describedembodiments have demonstrated the objective of increasing the share of acustomer's spending through the financial institution. One embodimenthas a marketing objective of increasing the customer's satisfaction withthe financial institution. For some embodiments, the marketing strategyobjective may be to help inculcate healthy spending habits in thecustomer in order to ensure financial stability and a long and healthyfinancial relationship with the financial institution.

Step 514 illustrates the input of marketing options into the marketingstrategy formulation method 500. Marketing options may include anythingthat the financial institution deems helpful in pursuing its marketingobjectives. These options pertain to, for example, both the manner inwhich marketing is conducted and the products or value propositionmarketed to the customer. In one embodiment, the marketing approachesinclude, but are not limited to, direct mail/catalog, online, outboundemail, outbound telemarketing, inbound calls, statements and accountmanagement, statement inserts, cell phone/text messaging, personalbankers conducting an interview with the customer, special recognitionat a bank or other entity, special ATM message, and special web sitemessage, for example. In accordance with one embodiment, the productsmarketed may have customized pricing schedules, cash back levels,partnerships with other businesses, travel programs, gift programs, orbe designed to adjust intelligently to the customer's evolvingbehaviors, for example.

In one embodiment, step 515 incorporates analytical outputs of othermethod steps such as potential credit card business into the marketingstrategy formulation method 500. Step 516 implements the marketingformulation decision engine 516. In one embodiment this decision engineperforms an optimization using known techniques to most effectivelyachieve the marketing objectives using the marketing options while notexceeding the marketing resource constraints. Various techniques areknown in the art for performing such processing, such as those describedin U.S. patent application Ser. No. 12/099,578, which is incorporated byreference herein in its entirety.

In one embodiment the invention produces multiple marketing strategy'sfor each customer. Step 517 then outputs the at least one marketingstrategy produced by the marketing formulation decision engine 517, andthen the process continues with step 600.

The processing for the above mentioned method steps is supported by thespend system 800 block diagram in FIG. 9. One embodiment of the analysismodule 810 of the spend system 800 is depicted in greater detail in FIG.11. The analysis module 810 includes a business analysis module 840. Thebusiness analysis module 840 further includes a data interface module842 and business analysis computing portion 842. The data interfacemodule 842 performs the function of an interface with other modules anddata portions of the spend system 800 (for example the data accessmodule 850 or the customer profile data store module 860). The datainterface module 842 therefore enables the business analysis module 840to isolate data or results helpful in the business related methods ofthe system, such as the determination of a customer's potential creditcard business. The business analysis computing portion 844 processes thedata obtained by the data interface module 842. In accordance with oneembodiment, these computations produce a customer's potential creditcard business.

Referring again to the block diagram of FIG. 12, one embodiment of thespend system 800 includes a marketing module 880. The marketing module880 further includes a data interface module 882. The data interfacemodule 882 performs the function of an interface with other modules anddata portions of the spend system 800 (for example the data accessmodule 850 or the customer profile data store module 860). The datainterface module 882 therefore enables the marketing module 880 toisolate data or results helpful in the marketing related methods of thesystem, such as the formulation of a marketing strategy.

The marketing module 880 further includes a user interface portion 888.The user interface portion 888 enables the manipulation of the marketingmodule 880 by a human or virtual user. In accordance with oneembodiment, the user interface portion 888 includes a computer terminalrunning a graphical interface through which a user may modify, provideinputs or retrieve outputs from the marketing module 880. The marketingconstraints portion 883, in accordance with one embodiment, containsconstraints relevant to the formulation of a marketing strategy. Theseconstraints may be provided by the user interface portion 888, forexample. Similarly, the marketing objectives portion 884 and themarketing options portion 885 within the marketing module 880 alsocontain information relevant to the formulation of a marketing strategy.Such information has been discussed previously with regards to theformulate marketing strategy step 600 in FIG. 1.

In accordance with one embodiment, the marketing strategy computingportion 887 performs processing to produce a marketing strategy. Theprocessing done by the marketing strategy computing portion 887 utilizesthe information in the other portions of the marketing module 880. Themarketing strategy may take a variety of forms. The marketing strategymay well target customers that have the potential for substantially morebusiness. For example, in accordance with one embodiment of theinvention, the marketing strategy might identify the potentialdifferential in spend of a customer. That is, the processing describedherein may identify customers that have a large spend in total, but asmall spend with the inquiring bank (i.e., the bank performing theassessment). Thus, the potential differential in spend is the differencebetween the total spend and the spend with the inquiring bank. Customersmight be targeted with a differential spend per year of more than aparticular number, such as $20,000, for example. Further, with suchcustomers, the marketing strategy may assess the best manner in which tocapture the additional spend. For example, if no gas is being purchasedwith the inquiring bank's card, then a gas card might be provided to thecustomer. In general, an approach is to identify the particular activityfor which spend is not being captured and provide marketing directly onpoint to the activity. Relatedly, the other card (or the issuer of theother card) might be identified, and the marketing material set out whythe inquiring bank's card is better vis-à-vis the other bank's card, orwhy the inquiring bank's card is better for a particular purpose. Inshort, the systems and methods of embodiments may deduce the best courseof action (e.g. the best offer) to extend so as to secure the additionalbusiness of the customer.

Step 600 in FIG. 1 depicts the execution of the marketing strategy(EMS), in accordance with one embodiment. The execution of the marketingstrategy involves the actual performance of at least some of the optionschosen by the MS. One embodiment performs execution of an individual'smarketing strategy in conjunction with the customized marketingstrategy's of other customers. Such coordination would allow foreconomies of scale with regards to marketing activities such as thedirect mail promotion of a single product package or the targeting ofgeographic clusters of customers.

In accordance with one embodiment, the marketing module 880 supports theexecution of a marketing strategy in accordance with the results of theformulation of the marketing strategy. Thus, the marketing module 880effects the various steps associated with the particular marketingstrategy. For example, based on the marketing strategy results, themarketing module 880 may control processing including effectingmailings, sending e-mails, prompting telephone communications, waitingfor predetermined time periods, controlling the sequence of whichchannels are used and when, and controlling the customers that arecontacted (and in what manner particular customers are contacted). Themarketing module 880, in implementing the marketing strategy, mayutilize other systems and/or dictate the action of persons through theuser interface portion, for example. In particular, the marketing module880 may take action based on certain trigger events, such as aparticular event or chain of events. For example, a particular triggerevent may result in a live chat session being extended to the customer.Based on the particular trigger event (or other information),participants in the chat session may be presented with relatedinformation. For example, a bank representative might be automaticallypresented with the subject matter of the particular item the customer isrequesting. Various other communications and action may be based ontrigger events and/or interrelated so as to be effected in concertvis-à-vis each other (or vis-à-vis some other event).

Accordingly, the marketing module 880 carries out the marketing strategyover some period of time. At a point in time, the execution of themarketing strategy will draw to a close, or at least be sufficientlyadvanced. Accordingly, in some embodiments, an update loop 700, asintroduced in FIG. 1 and shown in detail in FIG. 8, reevaluates othermethod steps in a continuous or occasional fashion. Step 712 shows howobserved changes of the customer's behavior (as indicated by ANCF orspending profile, for example) may trigger updates. Step 713 illustrateshow the update loop 700 includes observations of changes in factorsexternal to the customer. In one embodiment, the update loop 700observes a change in a customer's ANCF and re-determines the customer'sspending profile, potential credit card business and marketing strategyaccordingly. Such a change in ANCF may become apparent after a job loss,for example. Further, marriage or the birth of a child may change acustomer's spending profile and indicate an opportunity for the updateloop to reevaluate the marketing strategy for that customer. As a finalexample, step 713 may observe a change in gas prices and thereforeincorporate that information in the update loop 700. These changes, aswell as effects brought about by the execution of a marketing strategy,may trigger the update loop 700. One embodiment regularly employs theupdate loop 700 so that it is not dependent on a triggering event. Inone embodiment, the updating of the marketing strategy 714 and theexecution of the updated marketing strategy 715 occurs in a mannersimilar to the development of the original marketing strategy. Theupdate loop 700 updates the other method steps in a manner similar totheir original execution.

In accordance with one embodiment shown in FIG. 12, The data accessmodule 850 and the memory portion 870 work in conjunction to both storedata, provide processing and enable modules in the spend system toaccess data and computing resources. The data access module 850 providesaccess to data stored internally 852 to the system as well as dataexternal to the system 854. The storage of such data may be transitionedbetween the data access module 850 and the memory portion 870 dependenton the needs of the spend system 800. For example, data archived forlengthy periods of time may be transitioned from the data access module850 to the memory portion 870 and vice versa.

Data may take on a wide variety of forms as described herein, inaddition to those previously mentioned. Data stored internally mayinclude data representing one or more mathematical frameworks utilizedby processing modules within the spend system 800. Further, the dataaccess module 850 may include data relating to the variables used in theprocessing and computations of other modules, including values for thevariables.

A wide variety of data may processed by the systems and methods ofembodiments of the invention. Illustratively, for example, such data mayinclude time series data (e.g., data based on or relating to events andtime values associated with those events), data based on time of yearparameters, aggregated data (such as data aggregated at the individual,household, small business, or large business level, for example),merchant related data in general, customer related data in general, datareflecting various subsetting of data (such as subsetting out the mostrelevant activity), and data that is bounded in some manner (such as tocontrol outliers). Various other types of data may also be used in theprocessing described herein.

Various types of statistical analysis, including, in particular,probabilistic analysis and probabilistic modeling may be applied in thevarious processing as described herein. For example, based on data froma customer (or a number of customers) such data may estimate particularsregarding another customer. Such estimation may include a range ofcertainty, i.e., such estimation may include statistical boundaries ofcertainty. Thus, the another customer's spend capability might beestimated to be $3,000 per month, plus or minus $1,000. Based on suchrange of certainty, other analysis may then be performed on the anothercustomer. Accordingly, the various processing described herein may usediscreet values, ranges, and certainty parameters associated with suchdiscreet values and ranges.

As described above, FIGS. 9-14 show embodiments of structure and systemof the invention. Further, FIGS. 1-8 show various steps in accordancewith one embodiment of the invention. It is appreciated that the systemsand methods described herein may be implemented using a variety oftechnologies. Hereinafter, general aspects regarding possibleimplementation of the systems and methods of the invention will bedescribed.

It is understood that the system of the invention, and portions of thesystem of the invention, may be in the form of a “processing machine,”such as a general purpose computer, for example. As used herein, theterm “processing machine” is to be understood to include at least oneprocessor that uses at least one memory. The at least one memory storesa set of instructions. The instructions may be either permanently ortemporarily stored in the memory or memories of the processing machine.The processor executes the instructions that are stored in the memory ormemories in order to process data. The set of instructions may includevarious instructions that perform a particular task or tasks, such asthose tasks described above in the flowcharts. Such a set ofinstructions for performing a particular task may be characterized as aprogram, software program, or simply software.

As noted above, the processing machine executes the instructions thatare stored in the memory or memories to process data. This processing ofdata may be in response to commands by a user or users of the processingmachine, in response to previous processing, in response to a request byanother processing machine and/or any other input, for example.

As noted above, the processing machine used to implement the inventionmay be a general purpose computer. However, the processing machinedescribed above may also utilize any of a wide variety of othertechnologies including a special purpose computer, a computer systemincluding a microcomputer, mini-computer or mainframe for example, aprogrammed microprocessor, a micro-controller, a peripheral integratedcircuit element, a CSIC (Customer Specific Integrated Circuit) or ANCFIC(Application Specific Integrated Circuit) or other integrated circuit, alogic circuit, a digital signal processor, a programmable logic devicesuch as a FPGA, PLD, PLA or PAL, or any other device or arrangement ofdevices that is capable of implementing the steps of the process of theinvention.

It is appreciated that in order to practice the method of the inventionas described above, it is not necessary that the processors and/or thememories of the processing machine be physically located in the samegeographical place. That is, each of the processors and the memoriesused in the invention may be located in geographically distinctlocations and connected so as to communicate in any suitable manner.Additionally, it is appreciated that each of the processor and/or thememory may be composed of different physical pieces of equipment.Accordingly, it is not necessary that the processor be one single pieceof equipment in one location and that the memory be another single pieceof equipment in another location. That is, it is contemplated that theprocessor may be two pieces of equipment in two different physicallocations. The two distinct pieces of equipment may be connected in anysuitable manner. Additionally, the memory may include two or moreportions of memory in two or more physical locations.

To explain further, processing as described above is performed byvarious components and various memories. However, it is appreciated thatthe processing performed by two distinct components as described abovemay, in accordance with a further embodiment of the invention, beperformed by a single component. Further, the processing performed byone distinct component as described above may be performed by twodistinct components. In a similar manner, the memory storage performedby one distinct memory portion as described above may be performed bytwo memory portions.

Further, various technologies may be used to provide communicationbetween the various processors and/or memories, as well as to allow theprocessors and/or the memories of the invention to communicate with anyother entity; i.e., so as to obtain further instructions or to accessand use remote memory stores, for example. Such technologies used toprovide such communication might include a network, the Internet,intranet, Extranet, LAN, an Ethernet, or any client server system thatprovides communication, for example. Such communications technologiesmay use any suitable protocol such as TCP/IP, UDP, or OSI, for example.

As described above, a set of instructions is used in the processing ofthe invention. The set of instructions may be in the form of a programor software. The software may be in the form of system software orapplication software, for example. The software might also be in theform of a collection of separate programs, a program module within alarger program, or a portion of a program module, for example. Thesoftware used might also include modular programming in the form ofobject oriented programming. The software tells the processing machinewhat to do with the data being processed.

Further, it is appreciated that the instructions or set of instructionsused in the implementation and operation of the invention may be in asuitable form such that the processing machine may read theinstructions. For example, the instructions that form a program may bein the form of a suitable programming language, which is converted tomachine language or object code to allow the processor or processors toread the instructions. That is, written lines of programming code orsource code, in a particular programming language, are converted tomachine language using a compiler, assembler or interpreter. The machinelanguage is binary coded machine instructions that are specific to aparticular type of processing machine, i.e., to a particular type ofcomputer, for example. The computer understands the machine language.

Any suitable programming language may be used in accordance with thevarious embodiments of the invention. Illustratively, the programminglanguage used may include assembly language, Ada, APL, Basic, C, C++,COBOL, dBase, Forth, Fortran, Java, Modula-2, Pascal, Prolog, REXX,Visual Basic, and/or JavaScript, for example. Further, it is notnecessary that a single type of instructions or single programminglanguage be utilized in conjunction with the operation of the system andmethod of the invention. Rather, any number of different programminglanguages may be utilized as is necessary or desirable.

Also, the instructions and/or data used in the practice of the inventionmay utilize any compression or encryption technique or algorithm, as maybe desired. An encryption module might be used to encrypt data. Further,files or other data may be decrypted using a suitable decryption module,for example.

As described above, the invention may illustratively be embodied in theform of a processing machine, including a computer or computer system,for example, that includes at least one memory. It is to be appreciatedthat the set of instructions, i.e., the software for example, thatenables the computer operating system to perform the operationsdescribed above may be contained on any of a wide variety of media ormedium, as desired. Further, the data that is processed by the set ofinstructions might also be contained on any of a wide variety of mediaor medium. That is, the particular medium, i.e., the memory in theprocessing machine, utilized to hold the set of instructions and/or thedata used in the invention may take on any of a variety of physicalforms or transmissions, for example. Illustratively, the medium may bein the form of paper, paper transparencies, a compact disk, a DVD, anintegrated circuit, a hard disk, a floppy disk, an optical disk, amagnetic tape, a RAM, a ROM, a PROM, a EPROM, a wire, a cable, a fiber,communications channel, a satellite transmissions or other remotetransmission, as well as any other medium or source of data that may beread by the processors of the invention.

Further, the memory or memories used in the processing machine thatimplements the invention may be in any of a wide variety of forms toallow the memory to hold instructions, data, or other information, as isdesired. Thus, the memory might be in the form of a database to holddata. The database might use any desired arrangement of files such as aflat file arrangement or a relational database arrangement, for example.

In the system and method of the invention, a variety of “userinterfaces” may be utilized to allow a user to interface with theprocessing machine or machines that are used to implement the invention.As used herein, a user interface includes any hardware, software, orcombination of hardware and software used by the processing machine thatallows a user to interact with the processing machine. A user interfacemay be in the form of a dialogue screen for example. A user interfacemay also include any of a mouse, touch screen, keyboard, voice reader,voice recognizer, dialogue screen, menu box, list, checkbox, toggleswitch, a pushbutton or any other device that allows a user to receiveinformation regarding the operation of the processing machine as itprocesses a set of instructions and/or provide the processing machinewith information. Accordingly, the user interface is any device thatprovides communication between a user and a processing machine. Theinformation provided by the user to the processing machine through theuser interface may be in the form of a command, a selection of data, orsome other input, for example.

As discussed above, a user interface is utilized by the processingmachine that performs a set of instructions such that the processingmachine processes data for a user. The user interface is typically usedby the processing machine for interacting with a user either to conveyinformation or receive information from the user. However, it should beappreciated that in accordance with some embodiments of the system andmethod of the invention, it is not necessary that a human user actuallyinteract with a user interface used by the processing machine of theinvention. Rather, it is contemplated that the user interface of theinvention might interact, i.e., convey and receive information, withanother processing machine, rather than a human user. Accordingly, theother processing machine might be characterized as a user. Further, itis contemplated that a user interface utilized in the system and methodof the invention may interact partially with another processing machineor processing machines, while also interacting partially with a humanuser.

It will be readily understood by those persons skilled in the art thatthe present invention is susceptible to broad utility and application.Many embodiments and adaptations of the present invention other thanthose herein described, as well as many variations, modifications andequivalent arrangements, will be apparent from or reasonably suggestedby the present invention and foregoing description thereof, withoutdeparting from the substance or scope of the invention.

Accordingly, while the present invention has been described here indetail in relation to its exemplary embodiments, it is to be understoodthat this disclosure is only illustrative and exemplary of the presentinvention and is made to provide an enabling disclosure of theinvention. Accordingly, the foregoing disclosure is not intended to beconstrued or to limit the present invention or otherwise to exclude anyother such embodiments, adaptations, variations, modifications orequivalent arrangements.

What is claimed is:
 1. A system for determining a capacity to spend of afinancial services customer, the system comprising: a memory module thatinputs and stores both customer profile data and retail data of thefinancial services customer, the customer profile data comprisingfinancial attributes of the financial services customer, and the retaildata including purchase information from purchases made by the financialservices customer; an analysis module, the analysis module configuredto: generate an estimated top-down available net cash flow of thefinancial services customer based on the customer profile data andretail data of the financial services customer, input data regarding acustomer control group, including financial attributes of controlcustomers in the customer control group; compare financial attributes ofthe financial services customer with financial attributes of the controlcustomers to determine similar control customers that possess similarattributes to the financial services customer; generate an estimatedbottom-up available net cash flow of the financial services customerbased on available net cash flows of the similar control customers;compare the estimated top-down available net cash flow to the estimatedbottom-up available net cash flow to yield an available net cash flowfor the financial services customer, wherein the available net cash flowof the financial services customer constitutes a capacity to spend ofthe financial services customer on a recurring basis; and a marketingmodule configured to: generate customized marketing material for thefinancial services customer based on the available net cash flow for thefinancial services customer, the marketing material including acustomized offer for at least one financial product; send the customizedmarketing material to the financial services customer; and receive anacceptance, from the financial services customer, of the customizedoffer for at least one financial product.
 2. The system of claim 1,wherein generating an estimated top-down available net cash flow of thefinancial services customer includes the analysis module: inputtingincome data and budgetary items data of the financial services customer,such data included in the customer profile data; and determining adifferential between the income data and budgetary items data, thedifferential being the available net cash flow.
 3. The system of claim2, wherein the income data includes identifying monies from salary,investments and gifts.
 4. The system of claim 2, wherein the analysismodule segregates data such that the budgetary items data and theestimated top-down available net cash flow does not include monthlyexpenses payable by a card-based transaction.
 5. The system of claim 4,wherein a card based transaction is constituted by either a transactioneffected using a credit card or a transaction effected by using a debitcard.
 6. The system of claim 1, wherein the analysis module determiningan available net cash flow of the financial services customer includesdetermining a breakdown between cash spend and credit card spend.
 7. Thesystem of claim 1, wherein the financial attributes of control customersinclude spending habits of the control customers.
 8. The system of claim1, wherein the control customers are constituted by persons who performall their financial card-based transactions via a single financialinstitution.
 9. The method of claim 1, wherein the comparing attributesof the customer with financial attributes of control customers todetermine similar control customers that possess similar attributes tothe financial services customer, includes: identifying a known attributeas a key parameter, retrieving the value of the key parameter of thefinancial services customer; identifying similar control customers whohave a similar value of the key parameter; estimating unknown parametersof the financial services customer based on attributes of the identifiedcontrol customers.
 10. The system of claim 1, the marketing modulegenerating marketing material includes identifying a particular activityfor which spend is not being captured and generating marketing on pointto the particular activity.
 11. The system of claim 10, the marketingmodule generating marketing material includes the marketing moduleeffecting an online chat session with the financial services customer.12. The system of claim 1, the marketing module generating marketingmaterial is performed in response to an observed trigger event.
 13. Acomputer implemented method for determining a capacity to spend of afinancial services customer, the method comprising: inputting andstoring, by a memory module, both customer profile data and retail dataof the financial services customer, the customer profile data includingfinancial attributes of the financial services customer, and the retaildata including purchase information from purchases made by the financialservices customer; generating, by an analysis module, an estimatedtop-down available net cash flow of the financial services customerbased on the customer profile data and retail data of the financialservices customer; inputting data regarding a customer control group,including financial attributes of control customers in the customercontrol group; comparing financial attributes of the financial servicescustomer with financial attributes of the control customers to determinesimilar control customers that possess similar attributes to thefinancial services customer; generating an estimated bottom-up availablenet cash flow of the financial services customer based on available netcash flows of the similar control customers; comparing the estimatedtop-down available net cash flow to the estimated bottom-up availablenet cash flow to yield an available net cash flow for the financialservices customer; wherein the available net cash flow of the financialservices customer constitutes the capacity to spend of the financialservices customer on a recurring basis; generating, by a marketingmodule, customized marketing material for the financial servicescustomer based on the available net cash flow for the financial servicescustomer, the marketing material including a customized offer for atleast one financial product; sending the customized marketing materialto the financial services customer; and receiving an acceptance, fromthe financial services customer, of the customized offer for at leastone financial product.
 14. The system of claim 1, wherein the analysismodule: produces a profile of the financial services customer'sfinancial information, the profile including an itemization of thefinancial services customer's monetary inflow and outflow; identifies aportion of the financial services customer's monetary flow eligible tobe conducted through a financial institution, the identification basedin part on the financial services customer's profile; and does notrequire direct input from the financial services customer.
 15. Thesystem of claim 1, wherein the analysis module: selects a study group ofcustomers from data, the data including at least one of the customerprofile data and the retail data of the financial services customer;observes the study group so as to produce a profile of each study groupcustomer's financial information; produces a mathematical representationof an interrelationship between study group customer's profiles and thedata; applies the mathematical representation to identified customersnot within the study group in order to estimate those identifiedcustomer's profiles; identifies a portion of each identified customer'smonetary flow eligible to be conducted through a financial institution,the identification based in part on the identified customer's profile;and does not require direct input from the customer.